Reinforcement Learning (and specifically REINFORCE algorithm) for one-round "games"
This seems like a multi-armed bandit problem (no states involved here). I had the same problem some times ago and I was advised to sample the output distribution M times, calculate the rewards and then feed them to the agent, this was also explained in this paper Algorithm 1 page 3 (but different problem &amp; different context). I honestly don't know if this will work for your case. You could also take a look at this example.